Lead AI Engineer, Data Solutions

Salesforce.com, Inc.
Chicago, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 260K

Job location

Chicago, United States of America

Tech stack

A/B testing
API
Artificial Intelligence
Airflow
Business Logic
Google BigQuery
ETL
Data Systems
Python
Machine Learning
Salesforce
Software Systems
Data Streaming
Supervised Learning
Delivery Pipeline
Large Language Models
Snowflake
Spark
Model Validation
Backend
Build Management
Machine Learning Operations
Api Design
Data Pipelines

Job description

We are looking for a Lead AI Engineer to build next-generation AI and ML systems at Salesforce. This role focuses on developing intelligent decisioning systems and building an agent flywheel-a system of feedback loops that continuously evaluate, optimize, and improve agent performance over time. This is an applied AI role with strong data and systems ownership. You will build models and agents and the data pipelines and evaluation loops that enable continuous learning in production. What You'll Do Build the Agent Flywheel

  • Design feedback loops that enable agents and ML systems to improve from real-world outcomes
  • Track outcomes (engagement, conversion, quality) and evaluate agent performance
  • Build pipelines that collect and structure agent traces into training and evaluation datasets
  • Drive continuous improvement via prompting, policies, model selection, and fine-tuning

Develop ML & Agent Systems

  • Build and deploy ML models (classification, ranking, forecasting, recommendation)
  • Design AI agents that combine LLM reasoning, tool usage, and ML decisioning
  • Implement reusable patterns for multi-step reasoning, tool orchestration, and structured outputs
  • Integrate models and agents into business-critical workflows

Own Data & Model Pipelines

  • Design and build scalable data pipelines (batch and near real-time) for training, evaluation, and inference
  • Transform raw interaction data into features, labels, and evaluation datasets
  • Enable continuous retraining and evaluation through tightly coupled data + model pipelines
  • Ensure data quality, consistency, and reliability

Evaluation & Experimentation

  • Build offline and online evaluation frameworks
  • Develop evaluation datasets, golden traces, and regression-style test sets
  • Run A/B experiments and track key metrics (quality, revenue impact, latency, etc.)
  • Use production signals to drive continuous optimization

Systems & API Development

  • Build scalable Python services and APIs powering agent workflows
  • Collaborate with platform teams while owning application-level systems
  • Ensure reliability, observability, and performance

Requirements

  • 6+ years in AI/ML engineering or applied data science
  • Strong Python experience in production systems
  • Proven experience building and deploying ML models
  • Experience building data pipelines (ETL/ELT, batch or streaming)
  • Experience with APIs and backend systems

Agent & LLM Experience

  • Experience with LLM-powered systems (prompting, orchestration, evaluation)
  • Familiarity with agent workflows and tool usage
  • Experience with evaluation loops, agent traces, or iterative improvement systems preferred

Data & Systems Expertise

  • Experience building data pipelines supporting ML systems
  • Familiarity with tools like Spark, Airflow/Dagster, Snowflake/BigQuery
  • Understanding of data quality, lineage, and reproducibility

Modeling & Experimentation

  • Strong understanding of supervised learning and evaluation methods
  • Experience with A/B testing and experimentation
  • Ability to design systems combining ML, LLMs, and business logic, * Experience with agent improvement systems (scoring, optimization loops)
  • Exposure to evaluation tools (e.g., LangSmith, Braintrust, or similar)
  • Experience with large-scale experimentation platforms
  • Familiarity with enterprise SaaS or CRM

Benefits & conditions

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is, $172,500 -

About the company

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

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